Data characterization using visualization based on Customer Buying Pattern by Association Rule Mining Algorithms

Authors

  • U. Suba  MCA Student Department of Computer Applications,Anna University ,BIT Campus,Tiruchirappalli, India
  • R. Karthiyayini  Assistant professor, Department of Computer Applications, Anna University, BIT Campus, Tiruchirappalli, India

Keywords:

Business Intelligence ,Hidden Pattern,Market Based Analysis, Apriori Algorithm ,All Electronic Data Repository

Abstract

Association rule mining is a data mining technique which consists of variety of algorithms to identify the relationships between the data set. Specifically Frequent pattern mining is a technique to find the association between the data set in any discipline. Using this technique the data miner can extract any kinds of hidden patterns in order to promote their discipline such as business intelligence, medical analysis, and scientific environment etc,. This system focused on business intelligence data where market basket analysis are performed by the Apriori algorithm already. In this system the data sets are constructed by the provision of AllElectronics data repository. The main goal of this system is for effective data summarization and characterization using visualization techniques.

References

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2018-04-30

Issue

Volume 3, Issue 5, May-June-2018

Section

Research Articles

License

Copyright (c) IJSRCSEIT

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
U. Suba, R. Karthiyayini, " Data characterization using visualization based on Customer Buying Pattern by Association Rule Mining Algorithms , IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 5, pp.416-422, May-June-2018.